In the following discussion certain articles and methods will be described for background and introductory purposes. Nothing contained herein is to be construed as an “admission” of prior art. Applicant expressly reserves the right to demonstrate, where appropriate, that the articles and methods referenced herein do not constitute prior art under the applicable statutory provisions. Recent advances in diagnostics have focused on less invasive mechanisms for determining disease risk, presence and prognosis. Diagnostic processes for determining genetic anomalies have become standard techniques for identifying specific diseases and disorders, as well as providing valuable information on disease source and treatment options.
The identification of cell free nucleic acids in biological samples such as blood and plasma allow less invasive techniques such as blood extraction to be used in making clinical decisions. For example, cell free DNA from malignant solid tumors has been found in the peripheral blood of cancer patients; individuals who have undergone transplantation have cell free DNA from the transplanted organ present in their bloodstream; and cell-free fetal DNA and RNA have been found in the blood and plasma of pregnant women. In addition, detection of nucleic acids from infectious organisms, such as detection of viral load or genetic identification of specific strains of a viral or bacterial pathogen, provides important diagnostic and prognostic indicators. Cell free nucleic acids from a source separate from the patient's own normal cells can thus provide important medical information, e.g., about treatment options, diagnosis, prognosis and the like.
The sensitivity of such testing is often dependent upon the identification of the amount of nucleic acid from the different sources, and in particular identification of a low level of nucleic acid from one source in the background of a higher level of nucleic acids from a second source. Detecting the contribution of the minor nucleic acid species to cell free nucleic acids present in the biological sample can provide accurate statistical interpretation of the resulting data.
There is thus a need for processes for calculating copy number variation (CNV) in one or more genomic regions in a biological sample using information on contribution of nucleic acids in the sample. The present invention addresses this need.